Enterprise AI That Knows Your Business — Privately
Employees need AI assistance grounded in company knowledge — but enterprise data can't flow to public LLMs. ElixirData's Private AI Assistant gives every employee a governed AI interface backed by the Context Graph, with structural data isolation, model routing, and complete decision traces
The Challenge
Employees Use Public AI With Enterprise Data Because No Alternative Exists
Shadow AI is a growing enterprise risk. Employees turn to public LLMs like ChatGPT because internal tools are unavailable, restricted, or lack necessary enterprise context
Public LLMs lack organizational context and policies
Internal AI tools often operate without governance
Data access and question permissions are unenforced
No visibility into AI-assisted decision-making
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Lack of Context
Public AI tools cannot access your org chart, policies, products, or customer data, producing generic answers that require manual validation
Ungoverned Internal AI
Internal AI deployments without a Context Graph cannot enforce who accesses data, which queries are allowed, or capture usage evidence
Shadow AI Risk
Employees use uncontrolled AI to draft contracts, analyze data, or make decisions, leaving no audit trail of context or influence
Missing Decision Visibility
Without structured oversight, organizations cannot track what AI said, what context it used, or how it affected outcomes
How It Works
How AI Agents and Context Graph Power Private AI
The Private AI Assistant runs on Context OS, providing employees AI access grounded in enterprise knowledge, governed by policy, and fully traceable for accountability
Enterprise Context Layer
The Context Graph delivers enterprise knowledge including org structure, products, policies, procedures, customer data, and domain expertise
Organizational knowledge grounding for AI responses
Policy-aware AI guidance and enforcement
Product and customer context integration
Outcome: Domain expertise retrieval for accurate answers
LLM Council & Routing
Simple questions use fast models, complex analyses use advanced models, and sensitive data routes to on-prem models. All routing is governed and traceable
Query classification by type and complexity
Cost-optimized AI model routing
Sensitivity-aware and on-prem model support
Outcome: Trace AI queries and routing decisions for accountability auditing
Governed Interactions
All AI interactions are fully governed by role-based data access, sensitive data protection, and complete Decision Traces
Role-scoped data access control
Sensitive data redaction and protection
Interaction Decision Traces for accountability
Outcome: Monitor AI usage and compliance continuously
Capabilities
What Private AI Assistant Gets With ElixirData
ElixirData provides enterprise-grounded AI, governed LLM access, structural data isolation, and full visibility into usage and compliance across all interactions
Enterprise-Grounded Responses
Every AI response is grounded in the Context Graph, including company policies, product details, organizational knowledge, and domain expertise
Employees receive answers tailored to company context rather than generic public knowledge
Deliver accurate, context-aware responses aligned with enterprise data and policies
Intelligent LLM Routing
Multi-model council routes queries to the optimal LLM based on complexity, sensitivity, cost, and capability
OpenAI, Anthropic, Google, Mistral, and on-prem models are accessible through a single governed interface
Optimize AI performance, cost, and security while maintaining compliance
Structural Data Isolation
Data classification is enforced at the Context Graph level so employees see only what their role permits
Sensitive data such as PII, financials, or trade secrets is structurally blocked from unauthorized access rather than filtered post-retrieval
Protect sensitive information and enforce strict role-based access
Interaction Traces
Every AI interaction produces a Decision Trace capturing the question, context retrieved, model used, and accessed data
Organizations gain full visibility into AI usage, providing accountability and audit-ready evidence for all enterprise interactions
Track and audit AI interactions for governance and compliance
Usage Analytics
Track how employees use AI, including common query types, department adoption, cost per department, and recurring knowledge gaps
These insights allow enterprises to optimize usage, reduce costs, and identify training opportunities for employees effectively
Gain actionable insights to improve adoption, reduce costs, and fill knowledge gaps
DLP & Content Governance
Outbound governance prevents employees from submitting sensitive data into AI prompts
Inbound governance ensures AI responses do not expose confidential information across role or department boundaries
Maintain enterprise data security and prevent accidental information leakage
Use Cases
Private AI Assistant Scenarios
ElixirData enables governed AI interactions across the enterprise, combining the Context Graph with AI agents to provide accurate answers, secure data access, and traceable decisions
Integrations
Connects to Your Existing Stack
ElixirData seamlessly integrates with the tools your development teams already use, including code generation, testing frameworks, security scanners, and deployment platforms
LLM Providers
Enterprise Platforms
Knowledge Sources
Identity & DLP
FAQ
Frequently Asked Questions
Three structural layers enforce AI governance: role-based access, outbound DLP, and routing sensitive queries only to approved models
The Private AI Assistant provides governed, enterprise-grounded AI with role-based access, optimized model routing, and Decision Traces, unlike a general-purpose internal ChatGPT
The LLM Council routes queries by complexity, cost, and sensitivity, using appropriate models and reducing AI expenses by 40-60%
Decision Traces and usage analytics provide full visibility into AI usage, data access, policy enforcement, and audit trails for compliance
Ready to Transform Private AI Assistant?
See how ElixirData's Context OS and AI agents deploy over your existing private ai assistant stack in 4 weeks